Impact of Stratigraphic and Sedimentological Heterogeneity on Hydrocarbon Recovery in Carbonate Reservoirs

Imperial Users onl

The Effect of Chemical and Physical Enhancers on Trolamine Salicylate Permeation through Rat Skin

Purpose: To achieve percutaneous delivery of trolamine salicylate to muscle and joints for the treatment of inflammatory muscle, tendon and joint diseases.Methods: Trolamine salicylate permeability parameters through rat skin were evaluated with and without chemical enhancers - Transcutol, eucalyptus oil, oleic acid and sodium lauryl sulfate – using the permeability cell technique.Results: The main barrier for trolamine salicylate permeability was the epidermis layer of the skin. Also, partitioning from the aqueous donor phase into the skin was the rate-limiting step for drug flux. Transcutol and eucalyptus oil were the most effective enhancers as they increased flux 11-fold. Sodium lauryl sulfate disrupted the lipid structure of the skin and thus increased diffusion coefficient 3-fold. Supersaturation technique did not increase flux. Propylene glycol in cosolvent system increased drug solubility in donor phase and partitioning.Conclusion: Trolamine salicylate exhibited less flux and diffusion coefficient through rat skin than salicylic acid due to its hydrophilic property. Partitioning from vehicle into skin was the rate-limiting step for trolamine salicylate permeability through rat skin.Keywords: Trolamine salicylate, Percutaneous absorption, Chemical enhancers, Supersaturation technique, Differential scanning calorimetryTropical Journal of Pharmaceutical Research December 2010; 9 (6): 541-54

IMPACT OF NURSES' PERFORMANCE EVALUATION BY THE COMPILATION METHOD ON THEIR JOB SATISFACTION: RESULTS OF A PILOT STUDY

Introduction: performance evaluation is as one of the principal tasks of managers to achieve organizational goals and promote the quality of services. It can have an impact on job satisfaction. This study aimed to determine the impact of performance evaluation by compilation method on nurses’ job satisfaction. Methods: forty eight nurses working in hospitals in Ramhormoz were enrolled with census. In the first phase, their job satisfaction was measured using JDI questionnaire. Then, before the intervention, samples were taught about the new way of compilation performance evaluating was made by researcher during a workshop session, then using the compilation evaluation form, their evaluation was for two months. At the end of the evaluation and feedback to subjects, again their job satisfaction were measured and job satisfaction scores after the intervention than before the intervention were compared and evaluated. Data were analyzed using the software SPSS-22. Results: The results of this study showed that the performance evaluation scores of subjects after intervention [researcher made compilation performance evaluation] compared to pre-intervention three dimensions work, colleagues and supervisors of JDI job satisfaction separately and as a whole increased and there are significant differences meaningful. The results showed that there are significant difference in the scores of size [P <0/001], supervisor [P <0/001], college [P = 0/002] and job satisfaction [P <0/001]. Conclusions: Using new evaluation methods for nurses according to the clinical situation not only will increase the job satisfaction but also will improve the quality of patient care. Its application for Nursing Management Changes in the traditional evaluation systems and using new nurses’ evaluation methods and involving all in the evaluation can increase the level of the quality of care services. The implementation of this new method promotes the sense of confidence and job satisfaction. Keywords: performance evaluation, nurse, job satisfaction

Challenges in Adopting Artificial Intelligence (AI) in HRM Practices: A study on Bangladesh Perspective

Main Objectives: The objective of this study is to assess HRM practices in Bangladesh, as well as This paper, has highlighted the importance, future challenges, and benefits of adopting artificial intelligence. Novelty: In Bangladesh, most of the HRM-related research conducted by focusing existing HR practices, this paper, therefore, sought to explain the next step of human resource management practices through the possibility of adopting artificial intelligence. Research Methods: The relevant information was collected from secondary sources, such as newspaper articles, books, and websites. Based on secondary sources, we explain HRM practices in Bangladesh, AI Significance, and challenges in the adaptation of AI. Contributions: This study will assist policymakers to pay attention to the benefits and importance of adopting AI in HRM practices in Bangladesh, besides further research can be conducted on employee perception and readiness of accepting AI. Conclusion: Human resource management practices focused on artificial intelligence have a great potential to enhance employee performance, talent development, learning and development, and employee retention, while also helping to minimize employee turnover. As Bangladesh is progressing and going to be a developing country by 2024, hence this is a high time to adapt AI to boost up HR function in the business organization

Evaluation of Serum PSA in Different Storage Environments

ABSTRACT Background and Objective: Prostate cancer is a prevalent disease around the world. Th

Determining the mental model of experts regarding the factors hindering the development of table tennis in Iran

Determining the mental model of experts regarding the factors hindering the development of table tennis in Iran. The purpose of this study is to determine the mental pattern of experts regarding the barriers to professional table tennis in Iran using Q methodology. The present study is applied in terms of purpose; In terms of exploratory nature; In terms of data collection, descriptive-survey, and due to application, Q methodology is a type of mixed research (quantitative-qualitative). The statistical population was veterans and elites in table tennis in Iran, from which 21 people were selected as participants through a combination of purposeful and unlikely sampling and snowball sampling. Participant sorting data were entered in SPSS software to identify the different mindsets of the participants using Q-factor analysis. Finally, the main deterrents in Iranian professional table tennis were prioritized based on nine mental patterns. These mental patterns were then discussed and interpreted. Finally, coping strategies were proposed

Association Study between Coronary Artery Disease and rs1333049 and rs10757274 Polymorphisms at 9p21 Locus in South-West Iran

Objective: Coronary artery disease (CAD) is a multi-factorial and heterogenic disease with atherosclerosis plaques formation in internal wall of coronary artery. Plaque formation results to limitation of the blood reaching to myocardium leading to appearance of some problems, such as ischemia, sudden thrombosis veins and myocardial infarction (MI). Several environmental and genetic factors are involved in prevalence and incident of CAD as follows: hypertension, high low density lipoprotein-cholesterol (LDL-C), age, diabetes mellitus, family history of early-onset heart disease and smoking. According to genome wide association studies (GWAS), five polymorphisms in the 9p21 locus seem to be associated with the CAD. We aimed to evaluate the remarkable association of two polymorphisms at 9p21 locus, rs1333049 and rs10757274, with CAD. Materials and Methods: This experimental study was conducted in Golestan, Aria Hospitals and Genetics Lab of Shahid Chamran University in the city of Ahvaz, Iran, in 2010- 2011. The collected blood samples belonging to 170 CAD patients (case group) and 100 healthy individuals (control group) were analyzed by tetra-primer amplification refractory mutation system (ARMS)-polymerase chain reaction (PCR) technique. The results were analyzed using software package used for statistical analysis (SPSS; SPSS Inc., USA) version 16. A value of p<0.05 and an odd ratio (OR) with 95% confidence intervals (CI) were considered significant. Results: The frequencies of CC, CG and GG genotypes for rs1333049 polymorphism in patients were 18.2, 65.3 and 16.5%, while in controls, the related values were 25, 67 and 8%, respectively. GG genotypes of rs1333049 polymorphism in CAD patients were more than control cases (OR: 0.354, 95%CI: 0.138-0.912, p=0.032). The frequencies of AA, AG and GG genotypes for rs10757274 in CAD patients were 8.2, 58.3 and 33.5%, while in controls, the related values were 35, 63 and 2%, respectively. GG Genotype in rs10757274 polymorphism in CAD patients was found more than control cases (OR: 0.014, 95% CI: 0.003 -0.065, p=0.0001). Conclusion: The rs1333049 polymorphism at 9p21 locus shows a weak association with CAD, whereas rs10757274 polymorphism reveals a significant association with CAD. These variants may help the identification of patients with increased risk for coronary artery disease

OAERP: a better measure than accuracy in discriminating a better solution for stochastic classification training

The use of accuracy metric for stochastic classification training could lead the solution selecting towards the sub-optimal solution due to its less distinctive value and also unable to perform optimally when confronted with imbalanced class problem. In this study, a new evaluation metric that combines accuracy metric with the extended precision and recall metrics to negate these detrimental effects was proposed. This new evaluation metric is known as Optimized Accuracy with Extended Recall-precision (OAERP). By using two examples, the results has shown that the OAERP metric has produced more distinctive and discriminating values as compared to accuracy metric. This paper also empirically demonstrates that Monte Carlo Sampling (MCS) algorithm that is trained by OAERP metric was able to obtain better predictive results than the one trained by the accuracy metric alone, using nine medical data sets. In addition, the OAERP metric also performed effectively when dealing with imbalanced class problems. Moreover, the t-test analysis also shows a clear advantage of the MCS model trained by the OAERP metric against its previous metric over five out of nine medical data sets. From the abovementioned results, it is clearly indicates that the OAERP metric is more likely to choose a better solution during classification training and lead towards a better trained classification model